Algebraic Approach for Recovering Topology in Distributed Camera Networks

Abstract

Camera networks are widely used for tasks such as surveillance, monitoring and tracking. In order to accomplish these tasks, knowledge of localization information such as camera locations and other geometric constraints about the environment (e.g. walls, rooms, and building layout) are typically considered to be essential. However, this information is not always required for many tasks such as estimating the topology of camera network coverage, or coordinate-free object tracking and navigation. In this paper we propose a simplicial representation (called CN-Complex) that can be constructed from discrete local observations from cameras, and utilize this novel representation to recover the topological information of the network coverage. We prove that our representation captures the correct topological information from network coverage for 2.5D layouts, and demonstrate their utility in simulations as well as a real-world experimental set-up. Our proposed approach is particularly useful in the context of ad-hoc camera networks in indoor/outdoor urban environments with distributed but limited computational power and energy.

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Document Details

Document Type
Technical Report
Publication Date
Jan 14, 2009
Accession Number
ADA538850

Entities

People

  • Edgar Lobaton
  • Parvez Ahammad
  • S. Shankar Sastry

Organizations

  • University of California, Berkeley

Tags

Communities of Interest

  • Air Platforms
  • C4I
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Automated Target Recognition
  • Computations
  • Computer Science
  • Convex Sets
  • Detection
  • Detectors
  • Identification
  • Mesh Networks
  • Navigation
  • Networks
  • Observation
  • Sensor Networks
  • Simulations
  • Target Recognition
  • Topology
  • Wireless Communications
  • Wireless Sensor Networks

Fields of Study

  • Computer science

Readers

  • Computer Vision.
  • Distributed Systems and Data Platform Development
  • Graph Algorithms and Convex Optimization.